1. Field of the Invention
This invention relates generally to the field of communication systems. More particularly, the invention relates to a system and method for distributed input-distributed output wireless communications using space-time coding techniques.
2. Description of the Related Art
Space-Time Coding of Communication Signals
A relatively new development in wireless technology is known as spatial multiplexing and space-time coding. One particular type of space-time coding is called MIMO for “Multiple Input Multiple Output” because several antennas are used on each end. By using multiple antennas to send and receive, multiple independent radio waves may be transmitted at the same time within the same frequency range. The following articles provide an overview of MIMO:
IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, VOL. 21, NO. 3, April 2003: “From Theory to Practice: An Overview of MIMO Space-Time Coded Wireless Systems”, by David Gesbert, Member, IEEE, Mansoor Shafi, Fellow, IEEE, Da-shan Shiu, Member, IEEE, Peter J. Smith, Member, IEEE, and Ayman Naguib, Senior Member, IEEE.
IEEE TRANSACTIONS ON COMMUNICATIONS, VOL. 50, NO. 12, December 2002: “Outdoor MIMO Wireless Channels: Models and Performance Prediction”, David Gesbert, Member, IEEE, Helmut Bölcskei, Member, IEEE, Dhananjay A. Gore, and Arogyaswami J. Paulraj, Fellow, IEEE.
Fundamentally, MIMO technology is based on the use of spatially distributed antennas for creating parallel spatial data streams within a common frequency band. The radio waves are transmitted in such a way that the individual signals can be separated at the receiver and demodulated, even though they are transmitted within the same frequency band, which can result in multiple statistically independent (i.e. effectively separate) communications channels. Thus, in contrast to standard wireless communication systems which attempt to inhibit multi-path signals (i.e., multiple signals at the same frequency delayed in time, and modified in amplitude and phase), MIMO can rely on uncorrelated or weakly-correlated multi-path signals to achieve a higher throughput and improved signal-to-noise ratio within a given frequency band. By way of example, MIMO technology achieves much higher throughput in comparable power and signal-to-noise ratio (SNR) conditions where a conventional non-MIMO system can achieve only lower throughput. This capability is described on Qualcomm Incorporated's (Qualcomm is one of the largest providers of wireless technology) website on a page entitled “What MIMO Delivers” at http://www.cdmatech.com/products/what mimo delivers.jsp: “MIMO is the only multiple antenna technique that increases spectral capacity by delivering two or more times the peak data rate of a system per channel or per MHz of spectrum. To be more specific, for wireless LAN or Wi-Fi® applications QUALCOMM's fourth generation MIMO technology delivers speeds of 315 Mbps in 36 MHz of spectrum or 8.8 Mbps/MHz. Compare this to the peak capacity of 802.11a/g (even with beam-forming or diversity techniques) which delivers only 54 Mbps in 17 MHz of spectrum or 3.18 Mbps/MHz.”
MIMO systems typically face a practical limitation of fewer than 10 antennas per device (and therefore less than 10× throughput improvement in the network) for several reasons:
1. Physical limitations: MIMO antennas on a given device must have sufficient separation between them so that each receives a statistically independent signal. Although MIMO throughput improvements can be seen with antenna spacing of even fractions of the wavelength,
the efficiency rapidly deteriorates as the antennas get closer, resulting in lower MIMO throughput multipliers.
See, for example, the following references:
[1] D.-S. Shiu, G. J. Foschini, M. J. Gans, and J. M. Kahn, “Fading correlation and its effect on the capacity of multielement antenna systems,” IEEE Trans. Comm., vol. 48, no. 3, pp. 502-513, March 2000.
[2] V. Pohl, V. Jungnickel, T. Haustein, and C. von Helmolt, “Antenna spacing in MIMO indoor channels,” Proc. IEEE Veh. Technol. Conf., vol. 2, pp. 749-753, May 2002.
[3] M. Stoytchev, H. Safar, A. L. Moustakas, and S. Simon, “Compact antenna arrays for MIMO applications,” Proc. IEEE Antennas and Prop. Symp., vol. 3, pp. 708-711, July 2001.
[4] A. Forenza and R. W. Heath Jr., “Impact of antenna geometry on MIMO communication in indoor clustered channels,” Proc. IEEE Antennas and Prop. Symp., vol. 2, pp. 1700-1703, June 2004.
Also, for small antenna spacing, mutual coupling effects may degrade the performance of MIMO systems.
See, for example, the following references:
[5] M. J. Fakhereddin and K. R. Dandekar, “Combined effect of polarization diversity and mutual coupling on MIMO capacity,” Proc. IEEE Antennas and Prop. Symp., vol. 2, pp. 495-498, June 2003.
[6] P. N. Fletcher, M. Dean, and A. R. Nix, “Mutual coupling in multi-element array antennas and its influence on MIMO channel capacity,” IEEE Electronics Letters, vol. 39, pp. 342-344, February 2003.
[7] V. Jungnickel, V. Pohl, and C. Von Helmolt, “Capacity of MIMO systems with closely spaced antennas,” IEEE Comm. Lett., vol. 7, pp. 361-363, August 2003.
[8] J. W. Wallace and M. A. Jensen, “Termination-dependent diversity performance of coupled antennas: Network theory analysis,” IEEE Trans. Antennas Propagat., vol. 52, pp. 98-105, January 2004.
[9] C. Waldschmidt, S. Schulteis, and W. Wiesbeck, “Complete RF system model for analysis of compact MIMO arrays,” IEEE Trans. on Veh. Technol., vol. 53, pp. 579-586, May 2004.
[10] M. L. Morris and M. A. Jensen, “Network model for MIMO systems with coupled antennas and noisy amplifiers,” IEEE Trans. Antennas Propagat., vol. 53, pp. 545-552, January 2005.
Moreover, as the antennas are crowded together, the antennas typically must be made smaller, which can impact the antenna efficiency as well.
See, for example, the following reference
[11] H. A. Wheeler, “Small antennas,” IEEE Trans. Antennas Propagat., vol. AP-23, n. 4, pp. 462-469, July 1975.
[12] J. S. McLean, “A re-examination of the fundamental limits on the radiation Q of electrically small antennas,” IEEE Trans. Antennas Propagat., vol. 44, n. 5, pp. 672-676, May 1996.
Finally, with lower frequencies and longer wavelengths, the physical size of a single MIMO device can become unmanageable. An extreme example is in the HF band, where MIMO device antennas may have to be separated from each other by 10 meters or more.
2. Noise limitations. Each MIMO receiver/transmitter subsystem produces a certain level of noise. As more and more of these subsystems are placed in close proximity to each other, the noise floor increases. Meanwhile, as increasingly more distinct signals need to be distinguished from each other in a many-antenna MIMO system, an increasingly lower noise floor is required.
3. Cost and power limitations. Although there are MIMO applications where cost and power consumption are not an issue, in a typical wireless product, both cost and power consumption are critical constraints in developing a successful product. A separate RF subsystem is required for each MIMO antenna, including separate Analog-to-Digital (A/D) and Digital-to-Analog (D/A) converters. Unlike many aspects of digital systems which scale with Moore's Law (an empirical observation, made by Intel co-founder Gordon Moore, that the number of transistors on an integrated circuit for minimum component cost doubles about every 24 months; source: http://www.intel.com/technology/mooreslaw/), such analog-intensive subsystems typically have certain physical structural size and power requirements, and scale in cost and power linearly. So, a many-antenna MIMO device would become prohibitively expensive and power consumptive compared to a single-antenna device.
As a result of the above, most MIMO systems contemplated today are on the order of 2-to-4 antennas, resulting in a 2-to-4× increase in throughput, and some increase in SNR due to the diversity benefits of a multi-antenna system. Up to 10 antenna MIMO systems have been contemplated (particularly at higher microwave frequencies due to shorter wavelengths and closer antenna spacing), but much beyond that is impractical except for very specialized and cost-insensitive applications.
Virtual Antenna Arrays
One particular application of MIMO-type technology is a virtual antenna array. Such a system is proposed in a research paper presented at European Cooperation in the field of Scientific and Technical Research, EURO-COST, Barcelona, Spain, Jan. 15-17, 2003: Center for Telecommunications Research, King's College London, UK: “A step towards MIMO: Virtual Antenna Arrays”, Mischa Dohler & Hamid Aghvami.
Virtual antenna arrays, as presented in this paper, are systems of cooperative wireless devices (such as cell phones), which communicate amongst each other (if and when they are near enough to each other) on a separate communications channel than their primary communications channel to the their base station so as to operate cooperatively (e.g. if they are GSM cellular phones in the UHF band, this might be a 5 GHz Industrial Scientific and Medical (ISM) wireless band). This allows single antenna devices, for example, to potentially achieve MIMO-like increases in throughput by relaying information among several devices in range of each other (in addition to being in range of the base station) to operate as if they are physically one device with multiple antennas.
In practice, however, such a system is extremely difficult to implement and of limited utility. For one thing, there are now a minimum of two distinct communications paths per device that must be maintained to achieve improved throughput, with the second relaying link often of uncertain availability. Also, the devices are more expensive, physically larger, and consume more power since they have at a minimum a second communications subsystem and greater computational needs. In addition, the system is reliant on very sophisticated real-time of coordination of all devices, potentially through a variety of communications links. Finally, as the simultaneous channel utilization (e.g. the simultaneous phone call transmissions utilizing MIMO techniques) grows, the computational burden for each device grows (potentially exponentially as channel utilization increases linearly), which may very well be impractical for portable devices with tight power and size constraints.